Experimentally acquired data typically includes noise in addition to signals representing information and/or events of interest. The noise represents undesired variations that are not related to the desired data. For example, the acquired data can include stochastic variations generated by interactions with the environment surrounding a measured system or a detector acquiring the data. Noise can be generated within the measured system by events that are unrelated to the information of interest. Noise may also be generated when the acquired data is transmitted or processed, for example, when it is digitized. Noise can be a significant problem with devices employing an array of sensors in which there are numerous sources of signals.
Interferometry can measure very small differences in lengths, distances and changes in dimension density and other properties by the interference of two waves of light for optical imaging and communication applications. Quantum Resonance Interferometry (QRI) delivers signal-to-noise enhancement by interference between a wave equation representation of both the sensor-specific noise model and unknown incoming data containing a potential target or event of interest. Within the QRI formalism, signal can represent a specific target signature of interest, and all other target nonspecific background (including sensor) noise and clutter can be noise. QRI hypothesizes signal as a disturbance to noise, and re-formulates target detection/discrimination problems to be developing a compact a noise model for sensor physics.